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<p>The position paper formulates nine theses on the future development of statistics education in the context of Data Science and Artificial Intelligence. It emphasizes Data &amp; Statistical Literacy, data quality and ethics, the integration of statistics and machine learning, and the strengthening of an independent didactics of statistics.</p><p>The discussion contributions broaden these perspectives: Christina Elmer highlights science communication and AI literacy; Helmut Küchenhoff emphasizes project-based learning and data protection; Christoph Weisser stresses industrial practice and organization-wide data competence; Göran Kauermann reflects on the interplay between statistics and data science; and Rolf Biehler and Karin Binder focus on didactical and institutional development.</p><p>The rejoinder takes up these impulses and underlines the interdisciplinary responsibility for shaping future-oriented statistics education.</p>

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Daten, Künstliche Intelligenz und Evidenz – neue Anforderungen an die Statistikausbildung an Hochschulen

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月22日

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  • Ursula Berger,
  • Rolf Biehler,
  • Karin Binder,
  • Christina Elmer,
  • Florian Ertz,
  • Thomas Hotz,
  • Sarah Huber,
  • Katja Ickstadt,
  • Göran Kauermann,
  • Helmut Küchenhoff,
  • Karsten Lübke,
  • Ralf Münnich,
  • Katharina Schüller,
  • Thomas Skill,
  • Claus Weihs,
  • Henrike Weinert,
  • Christoph Weisser

摘要

The position paper formulates nine theses on the future development of statistics education in the context of Data Science and Artificial Intelligence. It emphasizes Data & Statistical Literacy, data quality and ethics, the integration of statistics and machine learning, and the strengthening of an independent didactics of statistics.

The discussion contributions broaden these perspectives: Christina Elmer highlights science communication and AI literacy; Helmut Küchenhoff emphasizes project-based learning and data protection; Christoph Weisser stresses industrial practice and organization-wide data competence; Göran Kauermann reflects on the interplay between statistics and data science; and Rolf Biehler and Karin Binder focus on didactical and institutional development.

The rejoinder takes up these impulses and underlines the interdisciplinary responsibility for shaping future-oriented statistics education.